{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-1-d5736fbb7480>:15: UserWarning: Legend does not support 'a' instances.\n",
      "A proxy artist may be used instead.\n",
      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
      "  plt.legend(\"as\",\"ahg\")\n",
      "<ipython-input-1-d5736fbb7480>:15: UserWarning: Legend does not support 's' instances.\n",
      "A proxy artist may be used instead.\n",
      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
      "  plt.legend(\"as\",\"ahg\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码3-1\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "data=np.arange(0,10,0.01)\n",
    "plt.title(\"lines\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.xlim(0,10)\n",
    "plt.ylim(0,10)\n",
    "plt.xticks([0,3,5,7,8])\n",
    "plt.yticks([0,0.2,0.4,0.6,0.8,1])\n",
    "plt.plot(data,data**2)\n",
    "plt.plot(data,data**4)\n",
    "plt.legend(\"as\",\"ahg\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.         1.57079633 3.14159265 4.71238898]\n"
     ]
    }
   ],
   "source": [
    "print(np.arange(0,2*np.pi,np.pi/2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = np.arange(0, 100)\n",
    "\n",
    "plt.subplot(221)\n",
    "\n",
    "plt.plot(x, x)\n",
    "\n",
    "plt.subplot(222)\n",
    "\n",
    "plt.plot(x, -x)\n",
    "\n",
    "plt.subplot(223)\n",
    "\n",
    "plt.plot(x, x ** 2)\n",
    "\n",
    "#plt.subplot(224)\n",
    "\n",
    "#plt.plot(x, np.log(x))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-4-8a0e13ff9e57>:25: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  p1.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码3-2\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "rad=np.arange(0,np.pi*2,0.01)\n",
    "p1=plt.figure(figsize=(8,6),dpi=80)\n",
    "p1.add_subplot(2,2,1)\n",
    "plt.title(\"lines\")\n",
    "plt.xlabel(\"x\")#x轴名称\n",
    "plt.ylabel(\"y\")#y轴名称\n",
    "plt.xlim(0,2*np.pi)#x轴显示范围\n",
    "plt.ylim(-1,1)#y轴显示范围\n",
    "plt.plot(rad,np.sin(rad))\n",
    "plt.legend([\"sin\",\"cos\"])\n",
    "plt.xticks(np.arange(0,2*np.pi,np.pi/2))#生成坐标刻度\n",
    "\n",
    "ax1=p1.add_subplot(2,2,2)\n",
    "plt.title(\"lines\")\n",
    "plt.xlabel(\"x\")#x轴名称\n",
    "plt.ylabel(\"y\")#y轴名称\n",
    "plt.xlim(0,2*np.pi)#x轴显示范围\n",
    "plt.ylim(-1,1)#y轴显示范围\n",
    "plt.plot(rad,np.cos(rad))\n",
    "plt.legend([\"cos\"])\n",
    "plt.xticks(np.arange(0,2*np.pi,np.pi/2))#生成坐标刻度\n",
    "p1.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-fa5b71832e96>:17: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  p1.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码3-2\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "rad=np.arange(0,np.pi*2,0.01)\n",
    "p1=plt.figure(figsize=(8,6),dpi=80)\n",
    "ax1=p1.add_subplot(2,1,1)\n",
    "plt.title(\"lines\")\n",
    "plt.xlabel(\"x\")#x轴名称\n",
    "plt.ylabel(\"y\")#y轴名称\n",
    "plt.xlim(0,2*np.pi)#x轴显示范围\n",
    "plt.ylim(-1,1)#y轴显示范围\n",
    "plt.plot(rad,np.sin(rad))\n",
    "plt.plot(rad,np.cos(rad))\n",
    "plt.legend([\"sin\",\"cos\"])\n",
    "plt.xticks(np.arange(0,2*np.pi,np.pi/2))#生成坐标刻度\n",
    "plt.savefig(\"sin\")\n",
    "p1.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
